Many-Criteria Optimization and Decision Analysis State-of-the-Art, Present Challenges, and Future Perspectives /
This book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously – such as performance,...
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| Andre forfattere: | , , , |
| Format: | Electronisk eBog |
| Sprog: | engelsk |
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Cham :
Springer International Publishing : Imprint: Springer,
2023.
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| Udgivelse: | 1st ed. 2023. |
| Serier: | Natural Computing Series,
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| Fag: | |
| Online adgang: | https://doi.org/10.1007/978-3-031-25263-1 |
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| 245 | 1 | 0 | |a Many-Criteria Optimization and Decision Analysis |h [electronic resource] : |b State-of-the-Art, Present Challenges, and Future Perspectives / |c edited by Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin Purshouse. |
| 250 | |a 1st ed. 2023. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2023. | |
| 300 | |a 1 online resource (XIII, 360 p. 74 illus.). |b 63 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
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| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Natural Computing Series, |x 2627-6461 | |
| 505 | 0 | |a Chapter 1: Introduction to Many-Criteria Optimization and Decision Analysis -- Chapter 2: Key Issues in Real-World Applications of Many-Objective Optimisation and Decision Analysis -- Chapter 3: Identifying Properties of Real-World Optimisation Problems through a Questionnaire -- Chapter 4: Many-Criteria Dominance Relations -- Chapter 5: Many-Objective Quality Measures -- Chapter 6: Benchmarking -- Chapter 7: Visualisation for decision support in many-objective optimisation: state-of-the-art, guidance and future directions -- Chapter 8: Theoretical Aspects of Subset Selection in Multi-Objective Optimisation -- Chapter 9: Identifying Correlations in Understanding and Solving Multi-Objective Problems -- Chapter 10: Bayesian Optimization -- Chapter 11: A game theoretic perspective on Bayesian many-objective optimization -- Chapter 12: Heterogeneous Objectives: State-of-the-Art and Future Research -- Chapter 13: MACODA Ontology and Knowledge Management. | |
| 520 | |a This book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously – such as performance, cost, risk, sustainability, and quality. The field develops theory, methods and tools that can support decision makers in finding appropriate solutions when faced with many (typically more than three) such criteria at the same time. The book consists of two parts: key research topics, and emerging topics. Part I begins with a general introduction to many-criteria optimization, perspectives from research leaders in real-world problems, and a contemporary survey of the attributes of problems of this kind. This part continues with chapters on fundamental aspects of many-criteria optimization, namely on order relations, quality measures, benchmarking, visualization, and theoretical considerations. Part II offers more specialized chapters on correlated objectives, heterogeneous objectives, Bayesian optimization, and game theory. Written by leading experts across the field of many-criteria optimization, this book will be an essential resource for researchers in the fields of evolutionary computing, operations research, multiobjective optimization, and decision science. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Computer science. | |
| 650 | 0 | |a Operations research. | |
| 650 | 1 | 4 | |a Theory of Computation. |
| 650 | 2 | 4 | |a Operations Research and Decision Theory. |
| 700 | 1 | |a Brockhoff, Dimo. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Emmerich, Michael. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Naujoks, Boris. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Purshouse, Robin. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031252624 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031252648 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031252655 |
| 830 | 0 | |a Natural Computing Series, |x 2627-6461 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-25263-1 |
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| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||